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security-auditor安全审计员

Agent Skill

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

总安装

2,742

周安装

112

GitHub Stars

98

下载量

878
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:security-auditor(安全审计员)
来源仓库:https://github.com/erichowens/some_claude_skills
仓库路径:skills/security-auditor
安装命令:
npx skills add https://github.com/erichowens/some_claude_skills --skill security-auditor
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/erichowens/some_claude_skills --skill security-auditor

简介

代码级静态安全扫描,提前识别潜在漏洞和安全隐患。

  • 涵盖依赖漏洞检测、密钥泄露排查和 OWASP Top 10 合规检查。
  • 提供 actionable 修复建议和 stakeholder 安全态势报告生成。
  • 支持预部署审计和 PR 合并前的安全审查流程集成。
  • 使用时不能直接采信工具输出结果,必须人工复核关键发现项。

SKILL.md

Security Auditor

Comprehensive security scanning for codebases. Identifies vulnerabilities before they become incidents. Focuses on actionable findings with remediation guidance.

When to Use

Use for:

  • Pre-deployment security audits
  • Dependency vulnerability scanning
  • Secret/credential leak detection
  • Code-level SAST (Static Application Security Testing)
  • Security posture reports for stakeholders
  • OWASP Top 10 compliance checking
  • Pre-PR security reviews

Do NOT use for:

  • Runtime security (WAF, rate limiting) - use infrastructure tools
  • Network security/firewall rules - use cloud/DevOps skills
  • SOC2/HIPAA/PCI compliance - requires legal/organizational process
  • Penetration testing execution - this is detection, not exploitation

Quick Start

Full Security Audit

# Run comprehensive scan
./scripts/full-audit.sh /path/to/project

# Output: security-report.json + summary

Quick Checks

# Dependency vulnerabilities only
npm audit --json > deps-audit.json

# Secret detection only
./scripts/detect-secrets.sh /path/to/project

# OWASP check specific file
./scripts/owasp-check.py /path/to/file.js

Core Scanning Capabilities

1. Dependency Scanning

Package ManagerCommandSeverity Levels
npmnpm audit --jsoncritical, high, moderate, low
yarnyarn audit --jsonsame as npm
pippip-audit --format jsoncritical, high, medium, low
cargocargo audit --jsonsame

Decision Tree:

Critical severity found?
├── YES → Block deployment, immediate fix required
│   └── Check if patch available → npm audit fix --force
├── NO → High severity?
    ├── YES → Fix within sprint, document if deferred
    └── NO → Low/Moderate → Track, fix during maintenance

2. Secret Detection

High-Risk Patterns:

  • API keys: /[A-Za-z0-9_]{20,}/ near "key", "api", "secret"
  • AWS credentials: AKIA[0-9A-Z]{16}
  • Private keys: -----BEGIN (RSA|EC|OPENSSH) PRIVATE KEY-----
  • JWT tokens: eyJ[A-Za-z0-9_-]+\.eyJ[A-Za-z0-9_-]+\.[A-Za-z0-9_-]+
  • Connection strings: ://[^:]+:[^@]+@

Entropy Analysis:

  • Shannon entropy > 4.5 on strings > 20 chars = suspicious
  • Base64-encoded blobs in source = investigate

False Positive Handling:

Secret-like pattern found?
├── In test file? → Lower severity, document
├── In example/docs? → Check if placeholder
├── High entropy + near "password"/"secret" → High confidence
└── In .env.example? → Acceptable if placeholder values

3. OWASP Top 10 Static Analysis

#VulnerabilityDetection Pattern
A01Broken Access ControlMissing auth checks on routes
A02Cryptographic FailuresWeak algorithms (MD5, SHA1 for passwords)
A03InjectionUnparameterized queries, eval(), innerHTML
A04Insecure DesignHardcoded credentials, missing rate limits
A05Security MisconfigurationDebug mode in prod, default credentials
A06Vulnerable ComponentsKnown CVEs in dependencies
A07Auth FailuresWeak password policies, session issues
A08Integrity FailuresUnsigned updates, untrusted deserialization
A09Logging FailuresSensitive data in logs, missing audit trails
A10SSRFUnvalidated URL inputs to fetch/request

4. Language-Specific Checks

JavaScript/TypeScript:

  • eval(), new Function() - code injection
  • innerHTML, outerHTML - XSS vectors
  • document.write() - DOM-based XSS
  • child_process.exec() with user input - command injection
  • Regex without timeout - ReDoS vulnerability

Python:

  • pickle.loads() with untrusted data - arbitrary code execution
  • yaml.load() without Loader=SafeLoader - code injection
  • subprocess.shell=True - command injection
  • eval(), exec() - code injection
  • SQL string concatenation - SQL injection

SQL:

  • String concatenation in queries - SQL injection
  • LIKE '%' + input + '%' - injection via wildcards
  • Missing parameterization - critical vulnerability

Anti-Patterns

Anti-Pattern: Security by Obscurity

What it looks like: "Nobody will find this hardcoded password" Why wrong: Secrets in source always leak eventually Instead: Environment variables, secret managers, zero hardcoded secrets

Anti-Pattern: Audit Fatigue

What it looks like: 500 findings, all "medium", team ignores Why wrong: Critical issues buried in noise Instead: Prioritize by exploitability, start with critical/high only

Anti-Pattern: Fix Without Understanding

What it looks like: npm audit fix --force without review Why wrong: May introduce breaking changes, doesn't address root cause Instead: Review each fix, understand the vulnerability, test after

Anti-Pattern: One-Time Audit

What it looks like: "We did a security audit last year" Why wrong: New CVEs daily, code changes constantly Instead: CI/CD integration, weekly automated scans minimum

Security Report Format

{
  "summary": {
    "critical": 0,
    "high": 2,
    "medium": 5,
    "low": 12,
    "informational": 8
  },
  "findings": [
    {
      "id": "SEC-001",
      "severity": "high",
      "category": "A03:Injection",
      "title": "SQL Injection in user search",
      "location": "src/api/users.js:45",
      "description": "User input concatenated directly into SQL query",
      "evidence": "const query = `SELECT * FROM users WHERE name = '${input}'`",
      "remediation": "Use parameterized queries: db.query('SELECT * FROM users WHERE name = $1', [input])",
      "references": ["https://owasp.org/www-community/attacks/SQL_Injection"]
    }
  ],
  "recommendations": [
    "Implement parameterized queries across all database access",
    "Add input validation layer",
    "Enable SQL query logging for monitoring"
  ]
}

CI/CD Integration

GitHub Actions Example

security-scan:
  runs-on: ubuntu-latest
  steps:
    - uses: actions/checkout@v4
    - name: Run security audit
      run: |
        npm audit --json > audit.json
        ./scripts/detect-secrets.sh . > secrets.json
        ./scripts/generate-report.py
    - name: Fail on critical
      run: |
        if jq '.summary.critical > 0' report.json; then
          echo "Critical vulnerabilities found!"
          exit 1
        fi

Scripts (in scripts/ folder)

ScriptPurpose
full-audit.shComprehensive security scan
detect-secrets.shHigh-entropy string and pattern detection
owasp-check.pyOWASP Top 10 static analysis
generate-report.pyCombine findings into unified report

Expert vs Novice Approach

NoviceExpert
Runs audit once before releaseCI/CD integration, every commit
Focuses on tool output onlyUnderstands vulnerability context
Fixes everything or nothingTriages by exploitability
Uses one scannerLayers multiple tools
Ignores false positivesTunes detection rules

Success Metrics

MetricTarget
Critical/High pre-production0
Mean time to remediate critical< 24 hours
False positive rate< 10%
Scan coverage100% of deployable code

Reference Files

  • references/owasp-top-10-2024.md - Detailed OWASP guidance
  • references/secret-patterns.md - Comprehensive regex patterns
  • references/remediation-playbook.md - Fix guidance by vulnerability type
  • references/ci-cd-templates.md - Integration examples
  • scripts/ - Working security scanning scripts

Detects: Dependency CVEs | Secret leaks | Injection vulnerabilities | OWASP violations | Security misconfigurations

Use with: site-reliability-engineer (deployment gates) | code-review (PR security checks)

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

26.41%
按下载量换算232

Codex

23.37%
按下载量换算205

windsurf

18.67%
按下载量换算164

Antigravity

11.22%
按下载量换算99

OpenCode

8.4%
按下载量换算74

Cursor

3.67%
按下载量换算32

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

来源信息

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